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The Evolution of Blockchain Virtual Machine Architecture Towards an Enterprise Usage Perspective

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 984)


Virtualization in the context of blockchain systems represents an essential phase in the development and migration of services from public chains to enterprise logic. Most of the ongoing blockchain uses-cases are using the existing public ledgers, but for business products and services, there is a need for custom tailored solutions to ensure flexibility and security. The Ethereum Virtual Machine has opened new ways to solve problems that require a public proof by executing logic on a decentralized ecosystem. In a natural evolutive process, virtualization logic was shaped by numerous architectures and business requirements. Beside performance and scalability, enterprise virtual machines are starting to focus on features like: formal verification, execution of business logic, cross-domain rules, upgradable smart contracts, data privacy politics and audit tools. The current paper presents an introduction, an architectural walkthrough of the most relevant virtual machines that currently exist in the enterprise blockchain ecosystem and an analytical perspective on the future of industry ready VM’s.


  • Blockchain
  • Virtualization
  • Architecture

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  • DOI: 10.1007/978-3-030-19807-7_36
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This work is supported by the York University, Toronto, Canada through the Blockchain Lab at

This work is supported through the DiFiCIL project (contract no. 69/08.09.2016, ID P_37_771, web:, co-funded by ERDF through the Competitiveness Operational Programme 2014–2020.

This work was possible thanks to the open source communities of Ethereum, Insolar, NEO, EOS, Hyperledger and Zilliqa that offered the code, technical papers and explanations for all required details.

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Correspondence to Alexandru Butean .

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Tara, A., Ivkushkin, K., Butean, A., Turesson, H. (2019). The Evolution of Blockchain Virtual Machine Architecture Towards an Enterprise Usage Perspective. In: Silhavy, R. (eds) Software Engineering Methods in Intelligent Algorithms. CSOC 2019. Advances in Intelligent Systems and Computing, vol 984. Springer, Cham.

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